Machine Learning Applied Scientist (Co-op)

• Evaluate the ML Development Environment In your first month, review the current training and validation tools. Identify areas for performance or usability improvements and contribute one concrete change by mid-term. 
• Collaborate Cross-Functionally and Debug Model Issues Work with robotics and software engineers to understand deployment requirements and constraints. Assist in diagnosing issues with model performance observed during robotic testing or simulation, and help implement fixes or improvements. 
• Own and Deliver a Scoped ML Project Lead a focused initiative such as testing a new augmentation strategy, developing a lightweight evaluation tool, or experimenting with model modifications for improved robustness. Present outcomes with metrics and insights at the end of the term. 
• Support Research on a Strategic Vision Problem Join early investigations into longer-term capabilities, such as handling part occlusion or improving model behavior with similar-looking parts. Conduct benchmarking and literature review to inform future roadmap decisions. 

Culture and Situation Fit  

You’ll thrive if you value initiative, technical depth, and seeing data as a design lever, not just input. Apera AI is fast-paced, collaborative, and impact-driven. Engineers here build systems that make AI dependable in messy, real-world conditions  

 You’ll thrive here if you: 

• Want to apply ML to real-world problems in industrial automation. 
• Are excited to see your work influence how robotic systems are built and deployed. 
• Enjoy solving practical problems with research-informed tools. 

Qualifications 

• Proficiency in Python and machine learning frameworks (e.g., PyTorch). 
• Understanding of computer vision fundamentals (e.g., detection, segmentation, 3D geometry). 
• Familiarity with model training, tuning, and evaluation workflows. 
• Interest in robotics or applying ML in production-grade software. 

Bonus Experience (Not Required) 

• Experience with synthetic data generation or tools like Blender. 
• Exposure to 6-DoF pose estimation, point cloud processing, or depth sensing. 
• Experience working in Linux or Docker-based environments. 
• Familiarity with AWS services used in ML development workflows (e.g., S3, EC2, SageMaker).

The compensation for this co-op role is CAD $3,600 to $4,500 per month. This is your opportunity to gain hands-on learning experience in one of the fastest-growing industries at the intersection of robotics, AI, and industrial automation.

Note: Please ensure you upload both your resume and transcript, either combined into a single file or as separate files.